BIPM H6001: Bus Intel & Process Modelling

Transcription

1 Short Title: Full Title: Bus Intel & APPROVED Bus Intel & Module Code: BIPM H6001 Credits: 7.5 NFQ Level: 9 Field of Study: Management and administration Module Delivered in no programmes Reviewed By: FINBARR FEENEY Module Author: FINBARR FEENEY Module Description: The aims of this module are: To analyse the design and implementation of Business Intelligence Systems in supporting the decision support requirements in enterprises; to demonstrate a critical understanding of data mining techniques employed in business knowledge discovery; To apply business process modelling techniques using BPEL and BPEL4WS in the development and composition of Business Processes and Services. Learning Outcomes On successful completion of this module the learner will be able to: LO1 LO2 LO3 LO4 LO5 Evaluate the processes, tools and technologies used to implement data warehouses and data marts. Critically examine the techniques for modelling the data warehouse from a logical and physical perspective to assist the decision support requirements of an enterprise. Select and apply business intelligence tools to perform the types of analysis that are required by decision makers. Formulate appraisals on data mining applications and evaluate their methods and techniques. Define business processes that interact with external entities through web services operations defined and that manifest themselves as Web services defined by current specifications (for example WSDL). Pre-requisite learning Co-requisite Modules No Co-requisite modules listed

2 Module Content & Content (The percentage workload breakdown is inidcative and subject to change) % Data Warehousing Data warehouse logical design: star schemas, fact tables, dimensions, snowflake schemas, dimension hierarchies, data marts. Data warehouse physical design: partitioning, parallelism, compression, indexes, materialized views. Data extraction, transformation, loading integrating and refreshing. Business Intelligence and Data Mining Business Intelligence platforms. Ad hoc query capabilities Operational business report generation. BI Interactive Dashboards. Data mining approaches and applications. Data mining technologies and implementations. Techniques for mining large databases. Data mining standards. Business Process specification, design and modelling Domain expert business process modelling using (for example) BPEL. Hierarchical and graph-like control regimes for advanced manipulation of data needed to defined process and control flow. Breakdown % Course Work 10 Course Work Type Description Outcome addressed % of total Date Continuous The following is an indication of the CA component of this module in terms of typical CA tasks and how they are assessed: CA1 elapsed, individual 30%; CA2 elapsed, individual 35%; CA3 elapsed, individual 35%; CA1 Typical task: Given particular business requirements, design a data mart from a logical and physical perspective. Design and implement appropriate extraction, transformation and loading rules to populate the data mart using operational data sources available; CA2 Typical task: Using particular data sources, build a Business Intelligence (BI) metadata repository. Using BI client tools develop and produce appropriate responses to decision support questions as well as deciding on and using appropriate techniques to guide the knowledge discovery process; CA3 Typical task: Deriving a new business process using, for example, BEPL, to specify process flow, error handling and reporting, and utilizing Web Services BEPL XML to specify interface design n/a No End of Module Formal Examination IT Tallaght reserves the right to alter the nature and timings of assessment

3 Module Workload This module has no Full Time workload. This module has no Part Time workload.

4 Module Resources Required Book Resources Ralph Kimball, Margy Ross, Warren Thornthwaite, Joy Mundy, Bob Becker 2008, The Data Warehouse Lifecycle Toolkit, 2nd Edition Ed., Wiley Recommended Book Resources Robert Stackowiak, Joseph Rayman, Rick Greenwald 2007, Oracle Data Warehousing and Business Intelligence Solutions, Elsevier Digital Press Daniel T. Larose 2006, Data Mining Methods and Models, Wiley Carlo Vercellis 2009, Business Intelligence: Data Mining and Optimization for Decision Making, Wiley Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski, Lukasz A. Kurgan 2008, Data Mining: A Knowledge Discovery Approach, Springer Gavin JT Powell 2005, Oracle Data Warehousing Tuning for 10g, Elsevier Digital Press Daniel T. Larose 2004, Discovering Knowledge in Data: An Introduction to Data Mining, Wiley David Loshin 2003, Business Intelligence: The Savvy Manager's Guide (The Savvy Manager's Guides), Morgan Kaufmann Publishers Stephen Few, O Reilly 2008, Information Dashboard Design: The Effective Visual Communication of Data This module does not have any article/paper resources This module does not have any other resources

5